---
library_name: peft
license: apache-2.0
base_model: mistralai/Mistral-7B-Instruct-v0.3
tags:
- generated_from_trainer
model-index:
- name: Mistral_Ch_Text_Grand
  results: []
datasets:
- chaymaemerhrioui/autre771
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# Mistral_Ch_Text_Grand

This model is a fine-tuned version of [mistralai/Mistral-7B-Instruct-v0.3](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.3) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4386

## Model description

The model convert a user input into a detailed technical description 

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 4
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- num_epochs: 3
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.9051        | 0.2886 | 50   | 0.8378          |
| 0.6498        | 0.5772 | 100  | 0.6354          |
| 0.559         | 0.8658 | 150  | 0.5632          |
| 0.4766        | 1.1501 | 200  | 0.5298          |
| 0.4575        | 1.4387 | 250  | 0.4946          |
| 0.4517        | 1.7273 | 300  | 0.4729          |
| 0.4278        | 2.0115 | 350  | 0.4606          |
| 0.4048        | 2.3001 | 400  | 0.4517          |
| 0.4137        | 2.5887 | 450  | 0.4427          |
| 0.3779        | 2.8773 | 500  | 0.4386          |


### Framework versions

- PEFT 0.15.2
- Transformers 4.51.3
- Pytorch 2.6.0+cu124
- Datasets 2.14.4
- Tokenizers 0.21.1